Eurosurveillance

BACKGROUNDThe incidence of SARS-CoV-2 infections was not directly observed during the pandemic. We estimated incidences and the associated burden, through the infection fatality rate (IFR) and infection hospitalization rate (IHR), by jointly modeling seroprevalence, hospitalization, and mortality data. METHODSWe used a hierarchical Bayesian model to fit a spline, representing incidence, to the observed number of hospitalizations, deaths and seroprevalence results. Two cross-sectional seroprevalence studies on the prevalence of SARS-CoV-2 antibodies in the general population collected 37,235 samples in the age interval 18 to 74 years across 30 time points between March 2020 and January 2021. One study analyzed residual laboratory samples with the Euroimmun Anti-SARS-CoV-2 ELISA. The other study analyzed blood donor samples with the Wantai Ab ELISA. Data on the sensitivity and specificity of the serological tests were obtained from published research. Time-varying IFR and IHR estimates and their associated delay distributions were estimated within the same model. RESULTSBy the end of January 2021, we estimated 19% (95%CrI 18%-21%), 13% (95%CrI 12%-15%) and 11% (95%CrI 8%-13%) of the Belgian 18-49, 50-64 and 65-74 year-olds to have been infected with SARS-CoV-2. Infections occurred in two large waves with few infections in between. The first wave mostly affected the younger age group, with a peak weekly incidence of 2.0% (95%CrI 1.7%-2.3%) end of March 2020, while weekly incidences were more comparable during the second wave end of October 2020: 1.6% (95%CrI 1.2%-2%) for 65-74 year-olds and 2.8% (95%CrI 2.3%-3.3%) for 18-49 year-olds. Both the hospitalization and fatality rates declined over time. Among persons aged 65 to 74 years the hospitalization rate declined from 9.9% (95%CrI 7.2-13.2) to 5.1% (95%CrI 3.2-6.3) and fatality rates from 2.8% (95%CrI 2.0%-3.8%) to 1.3% (95%CrI 0.9%-1.7%). IHR and IFR were considerably lower in the younger age groups. CONCLUSIONDuring 2020, an estimated 16.2% (95%CrI 15.1%-17.3%) of the Belgian adult population was infected with SARS-CoV-2. These infections occurred primarily in two waves, one in March and another one in October 2020, with minimal transmission in between. Severe disease was more prevalent among older age groups and earlier on in 2020.

Since the emergence of Omicron, reinfections with SARS-CoV-2 have been rising. We estimated the risk of SARS-CoV-2 reinfection in the widely vaccinated French population, from January to August 2022. At nine weeks post-infection, the relative risk of reinfection, primary infection with pre-Delta variants being the reference group, was estimated at 0.43 [95%CI 0.40-0.47] if the primary infection was attributed to Delta, 0.21 [95%CI 0.19-0.24] with BA.1 and 0.17 [95% CI 0.15-0.18] with BA.2, and rapidly waned overtime. After a BA.1 primary infection the protection was similar against BA.2 or BA.4/5 reinfection.

Measures to restrict physical inter-personal contact in the community have been widely implemented during the COVID-19 pandemic. We studied determinants for infection with SARS-CoV-2 with the aim of testing the efficiency of such measures. We conducted a national matched case-control study among unvaccinated persons aged 18-49 years. Cases were selected among those testing positive for SARS-CoV-2 by RT-PCR over a five-day period in June 2021. Controls were selected from the national population register and were individually matched on age, sex and municipality of residence and had not previously tested positive. Cases and controls were interviewed via telephone about contact with other persons and exposures in the community. We included 500 cases and 529 controls and determined odds ratios (ORs) and 95% confidence intervals (95%CIs) by conditional logistical regression with adjustment for household size and immigration status. We found having had contact with another individual with a known infection as the main determinant for SARS-CoV-2 infection. Reporting close contact with an infected person who either had or did not have symptoms resulted in ORs of 20 (95%CI:9.8-39) and 8.5 (95%CI 4.5-16) respectively. In contrast, community exposures were generally not associated with disease; several exposures were negatively associated. Exceptions were: attending fitness centers, OR=1.4 (95%CI:1.0-2.0) and consumption of alcohol in restaurants or cafes, OR=2.3 (95%CI:1.3-4.2). For reference, we provide a timeline of non-pharmaceutical interventions in place in Denmark from February 2020 to March 2022. Fitness centers and alcohol consumption were mildly associated with infection, in agreement with findings of our similar study conducted six month earlier (Epidemiology & Infection 2021;150:e9.). Transmission of disease through involvement in community activities appeared to occur only rarely, suggesting that community restrictions in place were efficient. Instead, transmission appeared to primarily take place in a confined space via contact to known persons.

Isolating COVID-19 cases and quarantining their close contacts can prevent COVID-19 transmissions but also inflict harm. We analysed isolation and quarantine orders by the local public health agency in Berlin-Reinickendorf (Germany) and their dependence on the recommendations by the Robert Koch Institute, the national public health institute. Between 3 March 2020 and 18 December 2021 the local public health agency ordered 24603 isolations and 45014 quarantines (mean contacts per case 1.9). More days of quarantine per 100 inhabitants were ordered for children than for adults: 4.1 for children aged 0-6, 5.2 for children aged 7-17, 0.9 for adults aged 18-64 and 0.3 for elderly aged 65-110. The mean duration for isolation orders was 10.2 and for quarantine orders 8.2 days. We calculated a delay of 4 days between contact and quarantine order. 3484 of contact persons were in quarantine when they developed an infection. Our study quantifies isolation and quarantine orders, shows that children had been ordered to quarantine more than adults and that there were fewer school days lost to isolation or quarantine as compared to school closures. Our results indicate that the recommendations of the Robert Koch Institute had an influence on isolation and quarantine duration as well as contact identification and that the local public health agency was not able to provide rigorous contact tracing, as the mean number of contacts was lower than expected.

BackgroundREACT-1 is a community survey of PCR confirmed swab-positivity for SARS-CoV-2 among random samples of the population in England. This interim report includes data from the fifth round of data collection currently underway for swabs sampled from the 18th to 26th September 2020. MethodsRepeated cross-sectional surveys of random samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 160,000 people in each round of data collection. Collection of self-administered nose and throat swab for PCR and questionnaire data. Prevalence of swab-positivity by round and by demographic variables including age, sex, region, ethnicity. Estimation of reproduction number (R) between and within rounds, and time trends using exponential growth or decay model. Assessment of geographical clustering based on boundary-free spatial model. ResultsOver the 9 days for which data are available, we find 363 positives from 84,610 samples giving a weighted prevalence to date of 0.55% (0.47%, 0.64%) in round 5. This implies that 411,000 (351,000, 478,000) people in England are virus-positive under the assumption that the swab assay is 75% sensitive. Using data from the most recent two rounds, we estimate a doubling time of 10.6 (9.4, 12.0) days covering the period 20th August to 26th September, corresponding to a reproduction number R of 1.47 (1.40, 1.53). Using data only from round 5 we estimate a reproduction number of 1.06 (0.74, 1.46) with probability of 63% that R is greater than 1. Between rounds 4 and 5 there was a marked increase in unweighted prevalence at all ages. In the most recent data, prevalence was highest in the 18 to 24 yrs age group at 0.96% (0.68%, 1.36%). At 65+ yrs prevalence increased [~]7-fold between rounds 4 and 5 from 0.04% (0.03%, 0.07%) to 0.29% (0.23%, 0.37%). Prevalence increased in all regions between rounds 4 and 5, giving the highest unweighted prevalence in round 5 in the North West at 0.86% (0.69%, 1.06%). In London, prevalence increased [~]5-fold from 0.10% (0.06%, 0.17%) to 0.49% (0.36%, 0.68%). Regional R values ranged from 1.32 (1.16,1.50) in Yorkshire and the Humber to 1.63 (1.42, 1.88) in the East Midlands over the same period. In the most recent data, there was extensive clustering in the North West, Midlands and in and around London with pockets of clustering in other regions including the South West, North East and East of England. Odds of swab-positivity were [~]2-fold higher in people of Asian and Black ethnicity compared with white participants. ConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England among all regions and age groups, including those age groups at highest risk. Although there is evidence of a recent deceleration in the epidemic, current levels of prevalence will inevitably result in additional hospitalisations and mortality in coming weeks. A re-doubling of public health efforts is needed to return to a declining phase of the epidemic.

In Dec 2021-Feb 2022, an intense and unprecedented co-circulation of SARS-CoV-2 variants with high genetic diversity raised the question of possible co-infections between variants and how to detect them. Using 11 mixes of Delta:Omicron isolates at different ratios, we evaluated the performance of 4 different sets of primers used for whole-genome sequencing and we developed an unbiased bioinformatics method which can detect all co-infections irrespective of the SARS-CoV-2 lineages involved. Applied on 21,387 samples collected between weeks 49-2021 and 08-2022 from random genomic surveillance in France, we detected 53 co-infections between different lineages. The prevalence of Delta and Omicron (BA.1) co-infections and Omicron lineages BA.1 and BA.2 co-infections were estimated at 0.18% and 0.26%, respectively. Among 6,242 hospitalized patients, the intensive care unit (ICU) admission rates were 1.64%, 4.81% and 15.38% in Omicron, Delta and Delta/Omicron patients, respectively. No BA.1/BA.2 co-infections were reported among ICU admitted patients. Although SARS-CoV-2 co-infections were rare in this study, their proper detection is crucial to evaluate their clinical impact and the risk of the emergence of potential recombinants.

We analyzed over 40 years of bacteriological surveillance data to reveal a 4-fold increase in Group A streptococcal (GAS) meningitis in 2022 compared to the annual average of 1982-2021 (n=5/year). Already 10 GAS meningitis cases occurred in 2023 (until March 13th). Molecular typing revealed that 25 out-of-29 (86%) isolates received in 2022 and 2023 were emm1.0 (Figure 1). WGS analysis of 19 emm1.0 isolates (2019 until 20th December 2022) demonstrated that 15 out-of-19 (79%) isolates belonged to the toxicogenic M1UK lineage. Based on these observations, we urge clinicians to be vigilant regarding clinical sign of meningitis with invasive GAS infections, since this disease manifestation appears to have a higher than expected occurrence due to clonal replacement by the recently-emerged M1UK variant. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/23286423v3_fig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@12ea749org.highwire.dtl.DTLVardef@1e8c4e6org.highwire.dtl.DTLVardef@d6dd1forg.highwire.dtl.DTLVardef@4f26dc_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Number of received S. pyogenes CSF isolates with proportion of emm1.0, 2013-2023 (until March 13th). C_FIG

In fall 2021 in Finland, the recommendation to use face masks in schools for pupils ages 12 years and above was in place nationwide. Some cities recommended face masks for younger pupils as well. Our aim was to compare COVID-19 incidence among 10-12-year-olds between cities with different recommendations on the use of face masks in schools. COVID-19 case numbers were obtained from the National Infectious Disease Registry (NIDR) of the Finnish Institute for Health and Welfare, where clinical microbiology laboratories report all positive SARS-CoV-2 tests with unique identifiers in a timely manner, including information such as date of birth, gender, and place of residence. The NIDR is linked to the population data registry, enabling calculation of incidences. We compared the differences in trends of 14-day incidences between Helsinki and Turku among 10-12-year-olds, and for comparison, also among ages 7-9 and 30-49 by using joinpoint regression. According to our analysis, no additional effect seemed to be gained from this, based on comparisons between the cities and between the age groups of the unvaccinated children (10-12 years versus 7-9 years).

The objective of this study was to estimate vaccine effectiveness (VE) against COVID-19 hospitalization and ICU admission, per period according to dominating SARS-CoV-2 variant (Alpha and Delta), per vaccine and per time since vaccination. To this end, data from the national COVID-19 vaccination register was added to the national register of COVID-19 hospitalizations. For the study period 4 April - 29 August 2021, 15,571 hospitalized people with COVID-19 were included in the analysis, of whom 887 (5.7%) were fully vaccinated. Incidence rates of hospitalizations and ICU admissions per age group and vaccination status were calculated, and VE was estimated as 1-incidence rate ratio, adjusted for calendar date and age group in a negative binomial regression model. VE against hospitalization for full vaccination was 94% (95%CI 93-95%) in the Alpha period and 95% (95%CI 94-95%) in the Delta period. The VE for full vaccination against ICU admission was 93% (95%CI 87-96%) in the Alpha period and 97% (95%CI 97-98%) in the Delta period. VE was high in all age groups and did not show waning with time since vaccination up to 20 weeks after full vaccination.

In early May 2022 a global outbreak of monkeypox (MPX) started among persons without a travel history to regions known to be enzootic for monkeypox-virus. On August 8 2022, the Netherlands reported its 1000th monkeypox case representing a cumulative incidence of 55 per million population, one of the highest cumulative incidences worldwide. Here we describe the epidemiological characteristics and clinical presentation of the first 1000 monkeypox cases in the Netherlands, within the context of the public health response. Additionally, we explored risk factors for and estimated the protective effect of first-generation smallpox vaccine against more severe MPX. The first 1000 MPX cases, reported between May 20 and August 8 2022, were predominantly MSM aged 31-45 years. The vast majority of infections were acquired through sexual contact with casual partners in private or recreational settings including LGBTQIA+ venues in the Netherlands. This indicates that, although some larger upsurges occurred from point-source and/or travel related events, the outbreak is mainly characterised by sustained transmission within the Netherlands. More severe MPX was associated with having one or more comorbidities as well as having participated in more (3+) different sexual activities 21 days before symptom onset. We found a vaccine effectiveness of the prior first-generation smallpox vaccine against more severe MPX of 58% (95% CI 17-78%), suggesting moderate protection against more severe MPX symptoms on top of any possible protection by this vaccine against MPXV infection and disease.

The goal of this study was to estimate rates of SARS-CoV-2 carriership and viral loads in the general Antwerp population and to compare the estimated prevalences and incidences with governmental data (numbers of detected positive cases, stringency measure index) in order to evaluate the dynamics leading to the second wave. We used (pre)admission screening results from the major Antwerp hospitals for estimating community prevalences and incidences. 43.545 samples were included (April - November 2020). High SARS-CoV-2 carriership rates (mean week prevalence of 1.3%) were found in the general Antwerp population. 35.4% of positive cases carried high viral loads. Only a small proportion (15.3%) of the viral circulation was detected by the nationally implemented testing policy. In the weeks before the second Belgian wave, increasing prevalences and incidences were found, together with country-wide easing of restriction measures. In our opinion these findings have led to origin of the second viral wave.

BackgroundSeverity of SARS-CoV-2 infection may vary over time. Here, we estimate age-specific risks of hospitalization, ICU admission and death given infection in the Netherlands from February 2020 to June 2021. MethodsA nationwide longitudinal serology study was used to estimate numbers of infections in three epidemic periods (February 2020 - June 2020, July 2020 - February 2021, March 2021 - June 2021). We accounted for reinfections and, as vaccination started in January 2021, breakthrough infections among vaccinated persons. Severity estimates were inferred by combining numbers of infections with aligned numbers of hospitalizations and ICU admissions from a national hospital-based registry, and aligned numbers of deaths based on national excess all-cause mortality estimates. ResultsIn each period there was a nearly consistent pattern of accelerating, almost exponential, increase in severity of infection with age. The rate of increase with age was highest for death and lowest for hospitalization. In the first period, the overall risk of hospitalization, ICU admission and death were 1.5% (95%-confidence interval [CI] 1.3-1.8%), 0.36% (95%-CI: 0.31-0.42%) and 1.2% (95%-CI: 1.0-1.4), respectively. The risk of hospitalization was higher in the following periods, while the risk of ICU admission remained stable. The risk of death decreased over time, with a substantial drop among [≥]70-years-olds in February 2021 - June 2021. ConclusionThe accelerating increase in severity of SARS-CoV-2 with age remained intact during the first three epidemic periods in the Netherlands. The substantial drop in risk of death among elderly in the third period coincided with the introduction of COVID-19 vaccination.

This paper relates to data from the Wellcome Sanger Institute, UK, regarding Covid-19 genomic surveillance. We use a simple model to give point estimates of the effective reproduction numbers of the B.1.617.2 and B.1.1.7 lineages in England, from sequenced data as at 15 May 2021. Comparison with the estimated reproduction number of B.1.1.7 enables an estimate of the increased transmissibility of B.1.617.2. We conclude that it is almost certain that there is increased transmissibility that will rapidly lead to B.1.617.2 becoming the prevailing variant in the UK. The derived estimates of increased transmissibility have uncertainty relating to the actual distribution of the generation interval, but they do point, under present conditions of vaccination coverage and NPIs, to exponential growth of positive cases.

COVID-19 is an emerging infectious disease which has been declared a pandemic by the World Health Organisation. Due to limited testing capacity for this new virus, variable symptomatology the majority of infected showing non-specific mild or no symptoms it is likely current prevalence data is an underestimate. MethodsWe present an estimate of the number of cases of COVID-19 compared to the number of confirmed case in Italy based on the daily reported deaths and information about the incubation period, time from symptom onset to death and reported case fatality rate. ResultsOur model predicts that on the 31st of January 2020 when the first 3 infected cases had been identified by Italian authorise there were already nearly 30 cases in Italy, and by the 24th of February 2020 only 0.5% cases had been detected and confirmed by Italian authorities. While official statistics had 132 confirmed case we believe a more accurate estimate would be closer to 26000. With a case-doubling period of about 2.5 days.

COVID-19 point prevalence PCR community testing allows disease burden estimation. In a sample of London residents, point prevalence decreased from 2.2% (95%CI 1.4;3.5) in early April (reflecting infection around lockdown implementation) to 0.2% (95%CI 0.03-1.6) in early May (reflecting infection 3-5 weeks into lockdown). Extrapolation from reports of confirmed cases suggest that 5-7.6% of total infections were confirmed by testing during this period. These data complement seroprevalence surveys improving the understanding of transmission in London.

In March 2025, as part of on-going enhanced surveillance for mosquito-borne Orthoflaviviruses, West Nile virus (WNV) RNA was detected in two pools of female Aedes vexans collected in July 2023 in Nottinghamshire, England. Viral RNA detection was achieved via reverse transcription-qPCR. Sequencing and subsequent phylogenetic analysis of a 402 bp fragment indicated that the detections clustered with WNV lineage 1a. The exact origin of this virus remains unclear, but this finding indicates a historic WNV presence in the United Kingdom (UK). Surveillance has not provided evidence of further viral transmission to date.

BackgroundThe Dutch government introduced the CoronaMelder smartphone application for digital contact tracing (DCT) to complement manual contact tracing (MCT) by Public Health Services (PHS) during the 2020-2022 SARS-CoV-2 epidemic. Modelling studies showed great potential but empirical evidence of DCT and MCT impact is scarce. MethodsWe determined reasons for testing, and mean exposure-testing intervals by reason for testing, using routine data from PHS Amsterdam (1 December 2020 to 31 May 2021) and data from two SARS-CoV-2 rapid diagnostic test accuracy studies at other PHS sites in the Netherlands (14 December 2020 to 18 June 2021). Throughout the study periods, notification of DCT-identified contacts was via PHS contact-tracers, and self-testing was not yet widely available. ResultsThe most commonly reported reason for testing was having symptoms. In asymptomatic individuals, it was having been warned by an index case. Only around 2% and 2-5% of all tests took place after DCT or MCT notification, respectively. About 20-36% of those who had received a DCT or MCT notification had symptoms at the time of test request. Test positivity after a DCT notification was significantly lower, and exposure-test intervals after a DCT or MCT notification were longer, than for the above-mentioned other reasons for testing. ConclusionsOur data suggest that the impact of DCT and MCT on the SARS-CoV-2 epidemic in the Netherlands was limited. However, DCT impact might be enlarged if app use coverage is improved, contact-tracers are eliminated from the digital notification process to minimise delays, and DCT is combined with self-testing. Author summaryDuring the 2020-2022 SARS-CoV-2 epidemic, the Dutch government introduced digital contact tracing (DCT) using a smartphone application to complement manual contact tracing (MCT) by professional contact-tracers. Mathematical models had suggested that DCT could slow down virus spread by identifying more individuals with whom the smartphone user had been in close contact and by reducing notification and testing delays after exposure. We used data collected during the Dutch epidemic to evaluate whether this was indeed the case and found that DCT and MCT had limited impact. Only around 2% of all tests took place after a DCT notification, and 2-5% after a MCT notification depending on MCT capacity at the time. Test positivity was lower after a DCT notification, and exposure-test intervals were longer after a DCT or MCT notification, than for other reasons for testing. About 20-36% of those who had received a DCT or MCT notification had symptoms at the time of test request and might have tested anyway even without having received the notification. However, DCT impact might be enlarged in future epidemics if app use coverage is improved and all exposure-notification-testing delays are minimised (e.g. no involvement of professional contact tracers and enabling self-testing after DCT notification).

BackgroundNational epidemic dynamics of SARS-CoV-2 infections are being driven by: the degree of recent indoor mixing (both social and workplace), vaccine coverage, intrinsic properties of the circulating lineages, and prior history of infection (via natural immunity). In England, infections, hospitalisations and deaths fell during the first two steps of the "roadmap" for exiting the third national lockdown. The third step of the roadmap in England takes place on 17 May 2021. MethodsWe report the most recent findings on community infections from the REal-time Assessment of Community Transmission-1 (REACT-1) study in which a swab is obtained from a representative cross-sectional sample of the population in England and tested using PCR. Round 11 of REACT-1 commenced self-administered swab-collection on 15 April 2021 and completed collections on 3 May 2021. We compare the results of REACT-1 round 11 to round 10, in which swabs were collected from 11 to 30 March 2021. ResultsBetween rounds 10 and 11, prevalence of swab-positivity dropped by 50% in England from 0.20% (0.17%, 0.23%) to 0.10% (0.08%, 0.13%), with a corresponding R estimate of 0.90 (0.87, 0.94). Rates of swab-positivity fell in the 55 to 64 year old group from 0.17% (0.12%, 0.25%) in round 10 to 0.06% (0.04%, 0.11%) in round 11. Prevalence in round 11 was higher in the 25 to 34 year old group at 0.21% (0.12%, 0.38%) than in the 55 to 64 year olds and also higher in participants of Asian ethnicity at 0.31% (0.16%, 0.60%) compared with white participants at 0.09% (0.07%, 0.11%). Based on sequence data for positive samples for which a lineage could be identified, we estimate that 92.3% (75.9%, 97.9%, n=24) of infections were from the B.1.1.7 lineage compared to 7.7% (2.1%, 24.1%, n=2) from the B.1.617.2 lineage. Both samples from the B.1.617.2 lineage were detected in London from participants not reporting travel in the previous two weeks. Also, allowing for suitable lag periods, the prior close alignment between prevalence of infections and hospitalisations and deaths nationally has diverged. DiscussionWe observed marked reductions in prevalence from March to April and early May 2021 in England reflecting the success of the vaccination programme and despite easing of restrictions during lockdown. However, there is potential upwards pressure on prevalence from the further easing of lockdown regulations and presence of the B.1.617.2 lineage. If prevalence rises in the coming weeks, policy-makers will need to assess the possible impact on hospitalisations and deaths. In addition, consideration should be given to other health and economic impacts if increased levels of community transmission occur.

Public health surveillance stratifies populations into age groups to help identify threats and provide appropriate responses. However, there is considerable variation in the age groupings used for epidemiology both between and within countries. We evaluate the age groups (under 1, 1-4, 5-14, 15-44, 45-64, over 65 years) used for syndromic surveillance in England. Comparing the existing age grouping with alternatives and using syndromic data to suggest new age groupings that maximise the homogeneity within groups and heterogeneity between groups. Data between November 2011 and March 2024 was extracted from four syndromic systems including 79 different syndromic indicators. Correlations between time series for individual ages in years were used to calculate homogeneity of specific age groups and age groupings (collections of age groups that completely span 0 to 90 years). Young adolescents were identified as a specific age group with distinct trends different to younger children or older adolescents. The current age group of 5 to 14 years was found to be more heterogeneous that over age groups, even those with a much wider span. Also, the age group over 65 years was assessed to be too broad and would benefit from being split into those over 90 years and below. Thus, our recommendation is a new age grouping for syndromic surveillance consisting of under 1s, 1 to 4, 5 to 8, 9 to 17, 18 to 33, 34 to 50, 51 to 67, 68 to 89 and over 90 years.

We compared vaccine effectiveness (VE) against severe COVID-19 during calendar periods from December 2021 to March 2022 when Omicron BA.1 and BA.2, respectively, were the dominating virus variants in Scania county, Sweden. We used continuous density case-control sampling matched for sex and age, and with further adjustment for differences in comorbidities and prior infection. VE remained relatively stable after the transition from BA.1 to BA.2 among people with at least three doses but decreased markedly among those with only two doses. Protection from prior infection was also lower after the transition to BA.2. These findings suggest that booster vaccination is needed to maintain sufficient protection against severe COVID-19.